Dust detection method and apparatus for cleaning robot

ABSTRACT

A dust detection method and apparatus of a cleaning robot. The dust detection method involves acquiring a floor image as a current floor image of a predetermined place at a current location of the cleaning robot in the predetermined place; obtaining a difference image between the current floor image and a background image selected from a feature map consisting of a plurality of floor images of the predetermined place; and detecting a dusty area based on the difference image and adjusting a cleaning power of the cleaning robot.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority of Korean Patent ApplicationNo.2004-13569, filed on Feb. 27, 2004, in the Korean IntellectualProperty Office, the disclosure of which is incorporated herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a cleaning robot, and moreparticularly, to a dust detection method and apparatus which canincrease the efficiency of a cleaning process by automatically detectingdust on a floor, appropriately adjusting a cleaning power of a cleaningrobot, and appropriately modifying a cleaning path of the cleaningrobot.

2. Description of Related Art

Recently, a variety of mobile robots, which generally include a drivingmeans, sensors, and a travel controller and perform many usefulfunctions while autonomously operating, have been developed. Forexample, a cleaning robot is a cleaning device that collects dust anddirt on the floor while autonomously moving about the surface without auser's control. For a more efficient cleaning process, the cleaningrobot is required to correlate its cleaning power to the amount of dustand dirt on the floor.

Various dust detection techniques for a cleaning robot, which adjust thecleaning power of the cleaning robot based on a result of determiningthe amount of dust and dirt on the floor, are disclosed in U.S. Pat.Nos. 5,163,202, 5,233,682, and 6,023,814. More specifically, in U.S.Pat. No. 5,163,202, a light emitter and a light receptor are installedon a dust suction tube of a cleaning robot, and the amount of dust anddirt on the floor of a room is determined based on the amount of lightreceived by the light receptor. In U.S. Pat. No. 5,233,682, the amountof dust and dirt determined based on the amount of light received by thelight receptor, and the sizes of dust and dirt particles are alsomeasured based on a total amount of time required for dust and dirtparticles to pass through an optical passage. However, the dustdetectability of these two patented techniques may deteriorate after aperiod of use because there is a high probability of impurities beingaccumulated at the light receptor and the light emitter. In order tosolve this problem, U.S. Pat. No. 6,023,814 discloses a vacuum cleanerwhich includes a detection sensitivity correction unit installed at asuction passage.

All of the above patented techniques cannot determine whether dustparticles exist on the floor until they draw the dust through a suctionpassage. In addition, the above patented techniques detect dust withoutconsidering the state of the floor, and thus, the efficiency of acleaning process may deteriorate.

SUMMARY OF THE INVENTION

An aspect of the present invention provides a dust detection method andapparatus, which can increase the efficiency of a cleaning process byautomatically detecting dust on the floor, adjusting a cleaning power ofa cleaning robot, and modifying a cleaning path of the cleaning robot.

According to an aspect of the present invention, there is provided adust detection method of a cleaning robot. The dust detection methodincludes acquiring a floor image as a current floor image of apredetermined place at a current location of the cleaning robot in thepredetermined place; obtaining a difference image between the currentfloor image and a background image selected from a feature mapconsisting of a plurality of floor images of the predetermined place;and detecting a dusty area based on the difference image and adjusting acleaning power of the cleaning robot.

The feature map may be generated by causing the cleaning robot to removedust and dirt on the floor of the predetermined place, acquire floorimages of the predetermined place, and store, as a map, the acquiredfloor images and the respective locations of the cleaning robot providedby a localization system.

In the acquiring, an illumination unit of the cleaning robot may beturned on when acquiring the current floor image.

In the acquiring, a portion of the current floor image which needs to beprocessed may be determined based on the speed of the cleaning robot.

If the plurality of floor images of the feature map have no patterns,one of floor images may be selected as the background image, andotherwise, the obtaining may include performing template matching on thecurrent floor image and each of the plurality of floor images of thefeature map; comparing a maximum among similarities obtained as templatematching results with a predetermined reference value; and selecting oneof the plurality of floor images of the feature map corresponding to themaximum similarity as the background image if the maximum similarity islarger than the predetermined reference value and setting the cleaningpower of the cleaning robot to a maximum level if the maximum similarityis not larger than the predetermined reference value.

According to another aspect of the present invention, there is provideda dust detection apparatus of a cleaning robot. The dust detectionapparatus includes an image acquisition unit which acquires a floorimage as a current floor image of a predetermined place at a currentlocation of the cleaning robot in the predetermined place; and a controlunit which obtains a difference image between the current floor imageand a background image selected from among the plurality of floor imagesof the feature map, detects a dusty area based on the difference image,and adjusts the cleaning power of the cleaning robot.

According to another aspect of the present invention, there is provideda computer-readable recording medium encoded with processinginstructions for causing a processor to execute the aforesaid dustdetection method.

According to another aspect of the present invention, there is provideda cleaning robot, including: an image acquisition unit acquires floorimages of a predetermined place in which the cleaning robot moves whileperforming a cleaning process; an image processing unit which performstreatments on the acquired floor image; and a control unit which obtainsa obtain difference images between the acquired floor images and aplurality of floor images of a feature map, detects an area with the useof the difference images, and adjusts the cleaning power of the cleaningrobot.

According to another aspect of the present invention, there is provideda method of controlling a cleaning robot, including: loading a featuremap; detecting a dusty area; adjusting the cleaning power of thecleaning robot to a calculated cleaning power; determining whether thedusty area is larger than one grid, which is a maximum cleaning area ofthe cleaning robot in any location; moving the cleaning robot to a gridnearest to a current location, when the dusty area is determined to belarger than one grid, modifying an existing cleaning path, performs acleaning operation in the nearest grid, and upon completing the cleaningoperation, returning to the current location; performing a cleaningoperation by following an existing cleaning path when the dusty area issmaller than one grid, displaying grids which have already been cleanedand other grids which are yet to be cleaned by the cleaning robot; andjudging whether the cleaning robot has completed its cleaning operationin all grids zones and, when the cleaning robot has not yet completedits cleaning operation in all grids repeating the detecting, adjusting,determining, moving, performing, and judging.

According to another aspect of the present invention, there is provideda computer readable storage medium encoded with processing instructionsfor causing a processor to execute the aforesaid method of controlling acleaning robot.

Additional and/or other aspects and advantages of the present inventionwill be set forth in part in the description which follows and, in part,will be obvious from the description, or may be learned by practice ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

These and/or other aspects and advantages of the present invention willbecome apparent and more readily appreciated from the following detaileddescription, taken in conjunction with the accompanying drawings ofwhich:

FIG. 1 is a block diagram of a cleaning robot according to an exemplaryembodiment of the present invention;

FIG. 2 is a flowchart of a dust detection method according to anembodiment of the present invention;

FIG. 3 is a flowchart of a method of forming a feature map usable withthe method of FIG. 2;

FIG. 4 is a flowchart of a method of controlling a cleaning robotaccording to an embodiment of the present invention;

FIGS. 5A, 5B, and 5C illustrate patternless (solid) floor images, i.e.,a current floor image, a stored floor image, and a difference imagebetween the current floor image and the stored floor image,respectively; and

FIGS. 6A, 6B, 6C, and 6D are patterned floor images, i.e., a currentfloor image, a stored floor image, a floor image obtained throughnormalized correlation, and a difference image, and a difference imagebetween the current floor image and the stored floor image,respectively.

DETAILED DESCRIPTION OF EMBODIMENTS

Reference will now be made in detail to embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings, wherein like reference numerals refer to the like elementsthroughout. The embodiments are described below in order to explain thepresent invention by referring to the figures.

FIG. 1 is a block diagram of cleaning robot according to an exemplaryembodiment of the present invention. Referring to FIG. 1, the cleaningrobot includes an image acquisition unit 110, an image processing unit120, an illumination unit 130, a control unit 140, a memory 150, anodometry unit 160, a suction unit 170, and a driving unit 180.

The image acquisition unit 110 is installed on a lower portion of thecleaning robot and acquires floor images of a predetermined place, inwhich the cleaning robot moves around while performing a cleaningprocess. The image acquisition unit 110 may be a camera with a wideangle or super-wide angle lens (e.g., a fisheye lens).

The image processing unit 120 performs various treatments, such asdistortion compensation and pre-treatment processes, on the floor imageacquired by the image acquisition unit 110.

The illumination unit 130 is installed on the lower portion of thecleaning robot, and is turned on and off by the control unit 140whenever the image acquisition unit 110 acquires floor images.

The control unit 140 controls some of the elements of the cleaning robotby running a predetermined control program. The control unit 140 maycontrol the illumination unit 120 and the image acquisition unit 110 sothat the image acquisition unit 110 can acquire floor images, obtaindifference images between the acquired floor images and a plurality offloor images of a feature map stored in the memory 150, detect an areawith the use of the difference images, and adjust the cleaning power ofthe cleaning robot based on the size of the area that requires cleaning.

The memory 150 stores a plurality of floor images of the predeterminedplace and the respective locations of the cleaning robot in thepredetermined place as the feature map.

The odometry unit 160 determines the distance that the cleaning robothas moved. An encoder may be used as the odometry unit 160.

The suction unit 170, which is installed on the lower surface of thecleaning robot to come into direct contact with the floor of thepredetermined place, collects dust and dirt from the floor of thepredetermined place by an air suction.

The driving unit 180 drives driving motors (not shown) which areindependent of each other and under the control of the control unit 140such that one of the driving motors rotates in a forward direction andthe second driving motor rotates in a backward direction.

FIG. 2 is a flowchart of a dust detection method according to thepresent embodiment of the present invention. Referring concurrently toFIGS. 1 and 2, the illumination control is performed in operation S202.The illumination unit 130 is turned on slightly before the imageacquisition unit 110 acquires a floor image and is turned off slightlyafter the image acquisition unit 110 acquires the floor image. A currentfloor image acquired by the image acquisition unit 110 is input inoperation S204. The input rate of frames by the image acquisition unit110 may be several per second. Thereafter, in operation S206, whichportion (hereinafter, referred to as an image processing portion) of thecurrent floor image is to be processed by the image processing unit 120is determined based on the speed of the cleaning robot. Floor imagesconsecutively acquired by the image acquisition unit 110 when thecleaning robot moves at low speeds are likely to represent almost thesame portions of the floor, in which case, there is no need for theimage processing unit 120 to repeatedly process redundant portions ofthe floor images. For example, it is assumed that the cleaning robotmoves at 300 mm/sec, and the image acquisition unit 110 takes a 30 cm×20cm floor image every 33 ms. Since the cleaning robot moves about 1 cm(=300×0.033) every 33 ms, a portion of the current floor image rangingfrom the top of the current floor image to 3 cm below therefrom may bedetermined as the image processing portion.

The image processing portion includes three sub-portions, i.e., upperand lower sub-portions which are each 1 cm wide, and a middlesub-portion which is interpolated between the upper and lower portionsand also 1 cm wide. The middle sub-portion reflects the distance (Ω 1cm) the cleaning robot moved in 33 ms, and the upper and lowersub-portions are provided to compensate for a difference between 1 cmand the distance that the cleaning robot moved in 33 ms.

In operation S208, the image processing unit 120 performs a distortioncompensation treatment and pre-treatment on the portion of the currentfloor image to be processed.

In operation S210, it is determined based on a feature map whether thecurrent floor image has figures. The feature map is a map of a pluralityof floor images obtained at various locations on the floor. A method offorming the feature map will be described later with reference to FIG.3. If the current floor image is determined not to have patterns, one ofthe plurality of floor images of the feature map is selected as abackground image for the current floor image in operation S212, and thenthe dust detection method proceeds to operation S224. Here, thebackground image is an image selected from among the plurality of floorimages of the feature map, and then it is compared with the currentfloor image. FIG. 5A illustrates a current floor image not havingfigures, and FIG. 5B illustrates a stored floor image corresponding tothe current floor image.

If the current floor image is determined to have figures based on thefeature map, a template matching process is performed in operation S214.FIG. 6A illustrates a current floor image having figures, and FIG. 6Billustrates a stored floor image corresponding to the current floorimage.

A similarity y(s, t) is obtained by template matching a template imagewith the current floor image. Template matching based on a normalizedcorrelation is described by Rafael C. Gonzales and Richard E. Woods in“Digital Image Processing” (pp. 583-586,1992). The similarity y(s, t) isdefined by Equation (1) below: $\begin{matrix}{{r\left( {s,t} \right)} = \frac{\sum\limits_{x}^{\quad}\quad{\sum\limits_{y}\quad{\left\lbrack {{f\left( {x,y} \right)}{\overset{\_}{f}\left( {x,y} \right)}} \right\rbrack\left\lbrack {{w\left( {x\quad s} \right)},{\left( {y\quad t} \right)\overset{\_}{w}}} \right\rbrack}}}{\left\{ {\sum\limits_{x}^{\quad}\quad{\sum\limits_{y}\quad{\left\lbrack {{f\left( {x,y} \right)}\overset{\_}{f}\left( {x,y} \right)} \right\rbrack^{2}\quad{\sum\limits_{x}\quad{\sum\limits_{y}\quad\left\lbrack {{w\left( {{x\quad s},{y\quad t}} \right)}\quad\overset{\_}{w}} \right\rbrack^{2}}}}}} \right\}^{\frac{1}{2}}}} & (1)\end{matrix}$where w(x, y) denotes the template image, {overscore (w)} denotes anaverage of the values of pixels of the template image w(x, y), f(x, y)denotes the current floor image, and {overscore (f)}(x, y) denotes anaverage of the values of pixels in a predetermined portion of thecurrent floor image f(x, y) corresponding to the template image w(x, y)(i.e., on the feature map).

In operation S216, the similarity obtained as a result of the templatematching process is compared with a predetermined reference value. Ifthe similarity is larger than the predetermined reference value, one ofthe plurality of images of the feature map is selected as a backgroundimage in operation S218. FIG. 6C illustrates an image whose similarity,obtained as a result of normalized correlation-based template matching,is larger than the predetermined reference value. In operation S220, thedistance that the cleaning robot has moved is determined based on thelocation of the current floor image in the feature map. Accordingly, anerror in the distance that the cleaning robot has moved, calculated bythe odometry unit 160, can be compensated for based on the distance thatthe cleaning robot has moved, calculated in operation S220. Thereafter,the dust detection method proceeds to operation S224.

If the similarity is not larger than the predetermined reference value,it is determined that there is a large amount of dust and dirt on aportion of the floor corresponding to the current floor image. Thus, thecontrol unit 140 outputs a maximum cleaning power or a maximum cleaningarea in operation S222. If the suction unit 170 is formed as a singledevice, the control unit 140 outputs the maximum cleaning power. If thesuction unit is composed of a plurality of suction devices, the controlunit 140 outputs the maximum cleaning area and the maximum cleaningpower. Here, when the maximum cleaning area is output, a cleaningoperation is performed using all of the suction devices. The similaritymay be the same as or lower than the predetermined reference value dueto obstacles on the floor of the predetermined place other than dustparticles. This factor is taken into account when forming the featuremap.

In operation S224, a difference image between the current floor imageand the background image is obtained. FIG. 5C illustrates a differenceimage between the floor images of FIG. 5A and 5B, and FIG. 6Dillustrates a difference image between the floor images of FIGS. 6A and6B. The difference image between the current floor image and thebackground image is obtained by using Equation (2) below:d (x, y)=|f(x, y)−w(x, y)   (2)where f(x, y) denotes the current floor image, w(x, y) denotes thebackground image, and d(x, y) denotes the difference image between thecurrent floor image and the background image. Supposing that the currentfloor image perfectly matches with the background image, the differenceimage between the current floor image and the background image isobtained by subtracting a value of each pixel of the background imagefrom a value of a corresponding pixel of the current floor image andthen determining the absolute value of the subtraction results. Eachpixel of the difference image may have an RGB value or a grey level.

In operation S226, cleaning power and a dusty area are determined basedon the difference image. The dusty area is determined based on pixels ofthe difference image having an RGB value or grey level higher than apredetermined critical value, and the cleaning power is calculated basedon the total area of the dusty area. Cleaning powers for different areasof dusty areas can be stored in memory as a table.

Thereafter, in operation S228, the control unit 140 outputs the cleaningpower and the dusty area.

FIG. 3 is a flowchart of a method of forming a feature map according tothe present embodiment of the present invention. Referring to FIG. 3,the cleaning robot removes dust and dirt on the floor while cleaning thepredetermined place in operation S302. In operation S304, a currentfloor image is input to the cleaning robot by the image acquisition unit110. In operation S306, current location information of the cleaningrobot is received from a localization system (not shown). Thelocalization system is a system which takes an image of the ceiling ofthe predetermined place, in which the cleaning robot moves, detects anartificial mark from the ceiling image, and estimates the location andazimuth angle of the cleaning robot based on the location of theartificial mark or data provided by the odometry unit 160. Thereafter,in operation S308, it is determined whether the current floor image hasthe same pattern as a previous floor image stored in a feature map,i.e., whether the current floor image is identical with the previousfloor image. If the current floor image has the same pattern as theprevious floor image, the current floor image is integrated into theprevious floor image in the feature map in operation S310. In otherwords, the fact that the current floor image has the same pattern as theprevious floor image is recorded in the feature map as background imagedata without storing the current floor image in the memory 150, thusreducing the storage used in the memory 150, which stores the featuremap. Thereafter, the method proceeds to operation S314.

If the current floor image does not have the same pattern as theprevious floor image in the feature map, the current floor image and thecurrent location data of the cleaning robot are registered with thefeature map separately from the previous floor image in operation S312.

In operation S314, the feature map is updated by storing the currentlocation information of the cleaning robot, which is obtained inoperation S306, the previous floor image, into which the current floorimage is integrated in operation S310, and the current floor image,which is registered with the feature map separately from the previousfloor image in operation S312, in the memory 150. In operation S316, itis determined whether the formation of the feature map is complete.

If the formation of the feature map is incomplete, the current locationof the cleaning robot is detected again or estimated by the localizationsystem in operations S318 through S322. More specifically, when thecleaning robot moves, the distance that the cleaning robot moved ismeasured by the odometry unit 160 in operation S318. In operation S320,it is determined whether a current location of the cleaning robot hasbeen successfully detected. The new current location of the cleaningrobot is detected by using the artificial mark attached onto the ceilingof the predetermined place as a reference.

If the artificial mark is detected at the current location of thecleaning robot, an accumulated error between the distance that thecleaning robot moved, measured by the odometry unit 160, and thedistance that the cleaning robot moved, calculated based on the newcurrent location of the cleaning robot is removed, and then the currentlocation data of the cleaning robot stored in the feature map is updatedby using the new current location of the cleaning robot in operationS322. If the feature map is updated in operation S322 or if the newcurrent location of the cleaning robot is yet to be detected inoperation S320, the method returns to operation S302.

If the formation of the feature map is complete in operation S316, themethod ends. [0046 FIG. 4 is a flowchart of a method of controlling acleaning robot, which performs the dust detection method of FIG. 2,according to an embodiment of the present invention. Referring to FIG.4, a feature map, which is generated by using the method of forming afeature map of FIG. 3 and then stored in the memory 150, is loaded inthe control unit 140 in operation S402. Thereafter, as shown in FIG. 2,a dusty area is detected in operation S404. In operation S406, thecontrol unit 140 adjusts the cleaning power of the cleaning robot to acalculated cleaning power.

In operation S408, it is determined whether the dusty area is largerthan one grid, which is a maximum cleaning area of the cleaning robot inany location. If the dusty area is larger than one grid, the controlunit 140 adjusts the driving unit 180 to move the cleaning robot from acurrent grid zone where the cleaning robot is currently located inanother grid zone, which, like the current grid zone, overlaps the dustyarea and is nearest to the current grid zone, in operation S410. Inoperation S412, an existing cleaning path is modified, and the cleaningrobot performs a cleaning operation in the nearest grid zone to thecurrent grid zone. Once the cleaning robot completes the cleaningoperation in the nearest grid zone to the current grid zone, it returnsto its original location, i.e., the current grid zone, and then themethod proceeds to operation S416.

If the dusty area is smaller than one grid, the cleaning robot performsa cleaning operation by following the existing cleaning path inoperation S414. Thereafter, in operation S416, grid zones, which havealready been cleaned by the cleaning robot, and other grid zones, whichare yet to be cleaned by the cleaning robot, are displayed on a displayunit (not shown) installed at a main body of the cleaning robot. Thedisplay unit may be a liquid crystal display (LCD).

Thereafter, in operation S418, it is determined whether the cleaningrobot has completed its cleaning operation in all grid zones. If thecleaning robot has not yet completed its cleaning operation in all gridzones, the method returns to operation S404, and then the cleaning robotcontinues to perform its cleaning operation. Otherwise, the method ends.

Embodiments of the present invention can be realized ascomputer-readable codes written on a computer-readable recording medium.The computer-readable recording medium includes nearly all kinds ofrecording devices, on/from which data can be written/read by computersystems. For example, the computer-readable recording medium includes aROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical datastorage, and a carrier wave (e.g., data transmission through theInternet). The computer-readable recording medium can be distributedover a plurality of computer systems connected to one another via anetwork so that computer codes therein can be executed in adecentralized manner. Functional programs, codes, and code segments thatembody the present invention can be easily derived by those skilled inthe art.

According to the described embodiments of the present invention, it ispossible to enhance the performance of the cleaning robot by obtaining adifference image between an input image obtained at a current locationof the cleaning robot and a predetermined background image selected fromamong a plurality of images of a feature map, detecting whether there isdust and dirt on the floor of a predetermined place that requirescleaning by the cleaning robot, and enabling the cleaning robot toperform a cleaning operation based on the detection results. Inaddition, it is possible to compensate for an error between the distancethat the cleaning robot moved, calculated by an odometry unit of thecleaning robot, and the distance that the cleaning robot moved,calculated based on the location of the predetermined background imagein the feature map.

Although a few embodiments of the present invention have been shown anddescribed, it would be appreciated by those skilled in the art thatchanges may be made in these embodiments without departing from theprinciples and spirit of the invention, the scope of which is defined inthe claims and their equivalents.

1. A dust detection method of a cleaning robot, comprising: acquiring afloor image as a current floor image of a predetermined place at acurrent location of the cleaning robot in the predetermined place;obtaining a difference image between the current floor image and abackground image selected from a feature map including a plurality offloor images of the predetermined place; and detecting a dusty areabased on the difference image and adjusting a cleaning power of thecleaning robot.
 2. The dust detection method of claim 1, wherein thefeature map is generated by causing the cleaning robot to remove dustand dirt on the floor of the predetermined place, acquiring floor imagesof the predetermined place, and storing, as a map, the acquired floorimages and the respective locations of the cleaning robot provided by alocalization system.
 3. The dust detection method of claim 1, wherein,when the current floor image is identical to a previous floor imagealready stored in the feature map, that the identity of the currentfloor image with the previous floor image is displayed on the featuremap, otherwise, the current floor image is stored in the feature mapseparately from the previous floor image.
 4. The dust detection methodof claim 1, wherein, in the acquiring, an illumination unit of thecleaning robot is turned on when acquiring the current floor image. 5.The dust detection method of claim 1, wherein, in the acquiring, aportion of the current floor image which needs to be processed isdetermined based on the speed of the cleaning robot.
 6. The dustdetection method of claim 1, wherein, when the plurality of floor imagesof the feature map have no patterns, one of the plurality of floorimages is selected as the background image, otherwise, the obtainingincludes: performing template matching on the current floor image andeach of the plurality of floor images of the feature map; performingtemplate matching on the current floor image and each of the pluralityof floor images of the feature map; comparing a maximum amongsimilarities obtained as template matching results with a predeterminedreference value; and selecting one of the plurality of floor images ofthe feature map corresponding to the maximum similarity as thebackground image when the maximum similarity is larger than thepredetermined reference value and setting the cleaning power of thecleaning robot to a maximum level when the maximum similarity is notlarger than the predetermined reference value.
 7. The dust detectionmethod of claim 6, wherein in the selecting, when one of the pluralityof floor images of the feature map is selected as the background image,a distance that the cleaning robot has moved is calculated based on thelocation of the background image in the feature map, and an error in thecalculated distance that the cleaning robot moved is compensated for. 8.A computer-readable recording medium encoded with processinginstructions for causing a processor to execute a dust detection methodof a cleaning robot, the method comprising: acquiring a floor image as acurrent floor image of a predetermined place at a current location ofthe cleaning robot in the predetermined place; obtaining a differenceimage between the current floor image and a background image selectedfrom a feature map including a plurality of floor images of thepredetermined place; and detecting a dusty area based on the differenceimage and adjusting a cleaning power of the cleaning robot.
 9. A dustdetection apparatus of a cleaning robot, comprising: an imageacquisition unit which acquires a floor image as a current floor imageof a predetermined place at a current location of the cleaning robot inthe predetermined place; and a control unit which obtains a differenceimage between the current floor image and a background image selectedfrom among the plurality of floor images of a feature map having aplurality of floor images of the predetermined place, detects a dustyarea based on the difference image, and adjusts the cleaning power ofthe cleaning robot.
 10. The dust detection apparatus of claim 9, whereinthe feature map is generated by causing the cleaning robot to removedust and dirt on the floor of the predetermined place, acquire floorimages of the predetermined place, and store, as a map, the acquiredfloor images and the respective locations of the cleaning robot providedby a localization system.
 11. The dust detection apparatus of claim 9,wherein, when the current floor image is identical to a previous floorimage already stored in the feature map, the identity of the currentfloor image with the previous floor image is displayed on the featuremap, otherwise, the current floor image is stored in the feature mapseparately from the previous floor image.
 12. The dust detectionapparatus of claim 9, wherein, when the plurality of floor images of thefeature map have no figures, the control unit selects one of theplurality of floor images is selected as the background image,otherwise, the control unit performs template matching on the currentfloor image and each of the plurality of floor images of the featuremap, comparing a maximum among similarities obtained as templatematching results with a predetermined reference value, and selects oneof the plurality of floor images of the feature map corresponding to themaximum similarity as the background image when the maximum similarityis larger than the predetermined reference value and sets the cleaningpower of the cleaning robot to a maximum level when the maximumsimilarity is not larger than the predetermined reference value.
 13. Thedust detection apparatus of claim 12, wherein, when one of the pluralityof floor images of the feature map is selected as the background image,the control unit calculates a distance that the cleaning robot movedbased on the location of the background image in the feature map andcompensates for an error in the calculated distance that the cleaningrobot has moved.
 14. The dust detection apparatus of claim 9, furthercomprising an illumination unit which is turned on when the imageacquisition unit acquires the current floor image.
 15. The dustdetection apparatus of claim 9, further comprising a memory which storesthe feature map.
 16. A cleaning robot, comprising: an image acquisitionunit acquires floor images of a predetermined place in which thecleaning robot moves while performing a cleaning process; an imageprocessing unit which performs treatments on the acquired floor image;and a control unit which obtains a obtain difference images between theacquired floor images and a plurality of floor images of a feature map,detects an area with the use of the difference images, and adjusts thecleaning power of the cleaning robot.
 17. The cleaning robot of claim16, wherein the image acquisition unit may be a camera with a wide angleor super-wide angle lens (e.g., a fisheye lens).
 18. The cleaning robotof claim 17, wherein the treatments include distortion compensation andpre-treatment processes.
 19. The cleaning robot of claim 16, wherein thecontrol unit adjusts the cleaning power based on the size of the areathat requires cleaning.
 20. The cleaning robot of claim 16, furthercomprises an illumination unit which is turned on by the control unitwhen the image acquisition unit acquires floor images.
 21. The cleaningrobot of claim 16, further comprises a memory which stores a pluralityof floor images of the predetermined place and the respective locationsof the cleaning robot in the predetermined place as the feature map. 22.The cleaning robot of claim 16, further comprising an odometry unitwhich determines a distance that the cleaning robot has moved.
 23. Thecleaning robot of claim 22, wherein the odometry unit is an encoder. 24.A method of controlling a cleaning robot, comprising: loading a featuremap; detecting a dusty area; adjusting the cleaning power of thecleaning robot to a calculated cleaning power; determining whether thedusty area is larger than one grid, which is a maximum cleaning area ofthe cleaning robot in any location; moving the cleaning robot to a gridnearest to a current location, when the dusty area is determined to belarger than one grid, modifying an existing cleaning path, performs acleaning operation in the nearest grid, and upon completing the cleaningoperation, returning to the current location; performing a cleaningoperation by following an existing cleaning path when the dusty area issmaller than one grid, displaying grids which have already been cleanedand other grids which are yet to be cleaned by the cleaning robot; andjudging whether the cleaning robot has completed its cleaning operationin all grids zones and, when the cleaning robot has not yet completedits cleaning operation in all grids repeating the detecting, adjusting,determining, moving, performing, and judging.
 25. A computer-readablerecording medium encoded with processing instructions for causing aprocessor to execute a method of controlling a cleaning robot, themethod comprising: loading a feature map; detecting a dusty area;adjusting the cleaning power of the cleaning robot to a calculatedcleaning power; determining whether the dusty area is larger than onegrid, which is a maximum cleaning area of the cleaning robot in anylocation; moving the cleaning robot to a grid nearest to a currentlocation, when the dusty area is determined to be larger than one grid,modifying an existing cleaning path, performs a cleaning operation inthe nearest grid, and upon completing the cleaning operation, returningto the current location; performing a cleaning operation by following anexisting cleaning path when the dusty area is smaller than one grid,displaying grids which have already been cleaned and other grids whichare yet to be cleaned by the cleaning robot; and judging whether thecleaning robot has completed its cleaning operation in all grids zonesand, when the cleaning robot has not yet completed its cleaningoperation in all grids repeating the detecting, adjusting, determining,moving, performing, and judging.